|
24 | 24 | colorspaces as known_colorspaces, |
25 | 25 | convert_color, |
26 | 26 | ) |
27 | | -from mathics.builtin.drawing.image_internals import ( |
28 | | - convolve, |
29 | | - matrix_to_numpy, |
30 | | - numpy_flip, |
31 | | - numpy_to_matrix, |
32 | | - pixels_as_float, |
33 | | - pixels_as_ubyte, |
34 | | - pixels_as_uint, |
35 | | -) |
36 | 27 | from mathics.core.atoms import ( |
37 | 28 | Atom, |
38 | 29 | Integer, |
|
48 | 39 | from mathics.core.list import ListExpression |
49 | 40 | from mathics.core.symbols import Symbol, SymbolDivide, SymbolNull, SymbolTrue |
50 | 41 | from mathics.core.systemsymbols import SymbolRule, SymbolSimplify |
| 42 | +from mathics.eval.image import ( |
| 43 | + convolve, |
| 44 | + matrix_to_numpy, |
| 45 | + numpy_flip, |
| 46 | + numpy_to_matrix, |
| 47 | + pixels_as_float, |
| 48 | + pixels_as_ubyte, |
| 49 | + pixels_as_uint, |
| 50 | +) |
51 | 51 |
|
52 | 52 | SymbolColorQuantize = Symbol("ColorQuantize") |
53 | 53 | SymbolImage = Symbol("Image") |
@@ -1582,9 +1582,9 @@ def _linearize(a): |
1582 | 1582 | u = numpy.unique(a) |
1583 | 1583 | n = len(u) |
1584 | 1584 |
|
1585 | | - lower = numpy.ndarray(a.shape, dtype=numpy.int) |
| 1585 | + lower = numpy.ndarray(a.shape, dtype=int) |
1586 | 1586 | lower.fill(0) |
1587 | | - upper = numpy.ndarray(a.shape, dtype=numpy.int) |
| 1587 | + upper = numpy.ndarray(a.shape, dtype=int) |
1588 | 1588 | upper.fill(n - 1) |
1589 | 1589 |
|
1590 | 1590 | h = numpy.sort(u) |
@@ -1713,7 +1713,7 @@ def apply(self, image, stype, evaluation): |
1713 | 1713 | elif stype == "Bit16": |
1714 | 1714 | pixels = pixels_as_uint(pixels) |
1715 | 1715 | elif stype == "Bit": |
1716 | | - pixels = pixels.astype(numpy.int) |
| 1716 | + pixels = pixels.astype(int) |
1717 | 1717 | else: |
1718 | 1718 | return evaluation.message("ImageData", "pixelfmt", stype) |
1719 | 1719 | return from_python(numpy_to_matrix(pixels)) |
|
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